Experiments with the digital elevation data of Australia show that the proposed computing approach can effectively improve the parallel performance of focal statistics algorithms. The results also show that the approach has almost the same calculation accuracy as that of ArcGIS. The proposed approach also exhibits good scalability when the number of Spark executors in clusters is increased.The current study aimed to explore the entomopathogenic fungi associated with the larvae of Chilo suppressalis Walker, a serious pest of rice, in northern Iran. The collected specimens were cultured and identified through morphological and molecular methods. The 38 specimens were identified by microscopic examination and genetic sequencing of the ITS region as follows twenty-one isolates of Beauveria bassiana, five isolates of Akanthomyces lecanii, four isolates of Akanthomyces muscarious, three isolates of Metarhizium anisopliae, two isolates of Hirsutella subulata, two isolates of Trichoderma sp. and one isolate of Aspergillus sp. All the identified isolates were treated on the larvae through bioassay, evaluating the amount of hydrophobin and the activities of proteases, chitinases and lipase to find their virulence. Moreover, the percentage of thermotolerant and cold activity of the isolates were tested to determine their environmental persistence. The overall results revealed the isolates of B. bassiana, including BBRR1, BBAL1 and BBLN1 as the most virulent and environmental adaptive isolates among the fungi associated with C. suppressalis.The sub-humid native rainforest in Yucatan is one of the most endangered in Mexico. Cattle production is one of the main causes of land use change and silvopastoral systems are a feasible alternative. This work compares the sustainable performance of silvopastoral (native and intensive) and monoculture cattle farms in the state of Yucatan using the Sustainability Assessment for Food and Agriculture (SAFA) framework. Questionnaires and semi-structured interviews were applied in 9 farms. Responses were fed to the SAFA Tool to obtain sustainability polygons. Percentages of SAFA themes positively and negatively valuated were calculated. Native farms had positive ratings for Participation, Land, Biodiversity and Cultural Diversity, whereas intensive excelled on Holistic Management. Native farms had limited ratings for Decent Livelihood. Native farms (and one intensive silvopastoral farm) had the highest percentages of themes positively valuated compared to monocultures (and one intensive silvopastoral farm), which scored the lowest. Positive evaluations identified native systems as an option for sustainable production; however, areas of opportunity in all farms were discovered. This is the first comparative study using SAFA to evaluate differences in farming systems in the Mexican tropics, providing valuable information to generate policies and incentives on sustainable livestock production, as well as for improving evaluation tools for local application.Xylella fastidiosa is a xylem-limited bacterium phylogenetically related to the xanthomonads, with an unusually large and diversified range of plant hosts. To ascertain the origin of its peculiarities, its pan-genome was scanned to identify the genes that are not coherent with its phylogenetic position within the order Xanthomonadales. The results of the analysis revealed that a large fraction of the genes of the Xylella pan-genome have no ortholog or close paralog in the order Xanthomonadales. https://www.selleckchem.com/products/oxythiamine-chloride-hydrochloride.html For a significant part of the genes, the closest homologue was found in bacteria belonging to distantly related taxonomic groups, most frequently in the Betaproteobacteria. Other species, such as Xanthomonas vasicola and Xanthomonas albilineans which were investigated for comparison, did not show a similar genetic contribution from distant branches of the prokaryotic tree of life. This finding indicates that the process of acquisition of DNA from the environment is still a relevant component of Xylella fastidiosa evolution. Although the ability of Xylella fastidiosa strains to recombine among themselves is well known, the results of the pan-genome analyses stressed the additional relevance of environmental DNA in shaping their genomes, with potential consequences on their phytopathological features.Autism Spectrum Disorder (ASD) impacts 1 in 54 children in the US. Two-thirds of children with ASD display problem behavior. If a caregiver can predict that a child is likely to engage in problem behavior, they may be able to take action to minimize that risk. Although experts in Applied Behavior Analysis can offer caregivers recognition and remediation strategies, there are limitations to the extent to which human prediction of problem behavior is possible without the assistance of technology. In this paper, we propose a machine learning-based predictive framework, PreMAC, that uses multimodal signals from precursors of problem behaviors to alert caregivers of impending problem behavior for children with ASD. A multimodal data capture platform, M2P3, was designed to collect multimodal training data for PreMAC. The development of PreMAC integrated a rapid functional analysis, the interview-informed synthesized contingency analysis (IISCA), for collection of training data. A feasibility study with seven 4 to 15-year-old children with ASD was conducted to investigate the tolerability and feasibility of the M2P3 platform and the accuracy of PreMAC. Results indicate that the M2P3 platform was well tolerated by the children and PreMAC could predict precursors of problem behaviors with high prediction accuracies.This paper introduces a technique using a k-nearest neighbor (k-NN) classifier and hybrid features extracted from acoustic emission (AE) signals for detecting leakages in a gas pipeline. The whole algorithm is embedded in a microcontroller unit (MCU) to detect leaks in real-time. The embedded system receives signals continuously from a sensor mounted on the surface of a gas pipeline to diagnose any leak. To construct the system, AE signals are first recorded from a gas pipeline testbed under various conditions and used to synthesize the leak detection algorithm via offline signal analysis. The current work explores different features of normal/leaking states from corresponding datasets and eliminates redundant and outlier features to improve the performance and guarantee the real-time characteristic of the leak detection program. To obtain the robustness of leak detection, the paper normalizes features and adapts the trained k-NN classifier to the specific environment where the system is installed. Aside from using a classifier for categorizing normal/leaking states of a pipeline, the system monitors accumulative leaking event occurrence rate (ALEOR) in conjunction with a defined threshold to conclude the state of the pipeline.